Parsing as a Cue-Based Retrieval Model
Dotlacil, Jakub
(2021) Cognitive Science, volume 45, issue 8, pp. 1 - 60
(Article)
Abstract
This paper develops a novel psycholinguistic parser and tests it against experimental and corpus reading data. The parser builds on the recent research into memory structures, which argues that memory retrieval is content-addressable and cue-based. It is shown that the theory of cue-based memory systems can be combined with transition-based
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parsing to produce a parser that, when combined with the cognitive architecture ACT-R, can model reading and predict online behavioral measures (reading times and regressions). The parser's modeling capacities are tested against self-paced reading experimental data (Grodner & Gibson, 2005), eye-tracking experimental data (Staub, 2011), and a self-paced reading corpus (Futrell et al., 2018).
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Keywords: ACT-R, Computational psycholinguistics, Cue-based retrieval, Memory retrieval, Modeling reading data, Processing, Experimental and Cognitive Psychology, Cognitive Neuroscience, Artificial Intelligence
ISSN: 0364-0213
Publisher: Wiley-Blackwell
Note: Funding Information: Parts of this research have been presented at University of Düsseldorf, University of Groningen, Potsdam University, Utrecht University, LINGUAE seminar in Paris, and CUNY conference 2021. I would like to thank the audiences for their comments, questions, and suggestions. I would furthermore like to thank Jelmer Borst, Adrian Brasoveanu, Emmanuel Chemla, Richard Futrell, John Hale, Laura Kallmeyer, Rick Nouwen, Cory Shain, Garrett Smith, Jennifer Spenader, Shravan Vasishth, Jan Winkowski, and the reviewers and the editor of Cognitive Science. The research presented in this paper would not be possible without the Lisa Compute Cluster supported by SURFsara (www.surfsara.nl). The research was supported by the NWO grant VC.GW.17.112. Funding Information: Parts of this research have been presented at University of D?sseldorf, University of Groningen, Potsdam University, Utrecht University, LINGUAE seminar in Paris, and CUNY conference 2021. I would like to thank the audiences for their comments, questions, and suggestions. I would furthermore like to thank Jelmer Borst, Adrian Brasoveanu, Emmanuel Chemla, Richard Futrell, John Hale, Laura Kallmeyer, Rick Nouwen, Cory Shain, Garrett Smith, Jennifer Spenader, Shravan Vasishth, Jan Winkowski, and the reviewers and the editor of Cognitive Science. The research presented in this paper would not be possible without the Lisa Compute Cluster supported by SURFsara (www.surfsara.nl). The research was supported by the NWO grant VC.GW.17.112. Publisher Copyright: © 2021 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).
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